Financial influencers and the future of financial advice: a systematic review and thematic analysis
Devanshu MongaPurpose
The traditional financial advisory landscape has seen a paradigm shift with the advent of social media platforms and merchant broking platforms. This has created a new pool of influencers called financial influencers sharing investment guidance on social media platforms. This review aims to examine such financial influencers and their impact on dissemination of financial information and investment decisions.
Design/methodology/approach
A systematic review focussing on financial influencers is conducted using PRISMA protocol to extract and filter the relevant literature from three academic databases – Scopus, Web of Sciences and Dimensions.ai. A total of 25 relevant articles are shortlisted and analysed using TCCM framework and qualitative thematic analysis.
Findings
The theory of planned behaviour, expectation–confirmation model and technology acceptance model emerged as dominant theoretical frameworks. The studies are largely concentrated in countries such as Indonesia, the United States and India with YouTube, Instagram and Twitter (X) as common platforms. Key characteristics of financial influencers influencing investment decisions include credibility, quality of the information, expertise and engagement styles. Quantitative methods dominate the existing literature, although qualitative and mixed methods are also used in some studies. Thematic analysis highlights regulatory concerns of following such unregulated recommendations.
Research limitations/implications
The study focused on financial influencers or finfluencers to extract literature which limits our scope to only 25 articles. Future reviews could broaden this dimension by including more relevant keywords and databases for comprehensive coverage of literature.
Originality/value
The review is the first to apply TCCM framework along with thematic analysis in this field. It also identifies critical gaps in the literature, including long-term performance of stocks, and effectiveness of regulations, thereby paving the way for future empirical exploration.